Comparative Life Cycle Assessment of Reusable vs ......categories considered, the disposables’ impacts are mostly linked to raw materials and manufacturing. The reusable products’

Comparative Life Cycle

Assessment of Reusable vs.

Disposable Textiles

Doc. no. 1200473.000 8193

Comparative Life Cycle Assessment

of Reusable vs. Disposable Textiles

Prepared for

Textile Rental Services Association of America

188 Diagonal Road, Suite 200

Alexandria, VA 22314

Prepared by

John Jewell

PE International

344 Boylston Street, Third Floor

Boston, MA 02116

Randall Wentsel, Ph.D.

Exponent

1150 Connecticut Ave, NW, Suite 1100

Washington, DC 20036

August 7, 2014

Exponent, Inc.

1200473.000 - 8193 ii

Contents

Page

List of Figures v

List of Tables vi

Executive Summary vii

1 Goal of the Study 1

2 Scope of the Study 2

2.1 Product Systems to be Studied 2

2.2 Functional Unit and Reference Flows 2

2.3 System Boundaries 3

2.3.1 Time Coverage 3

2.3.2 Technology Coverage 3

2.3.3 Geographic Coverage 4

2.4 Allocation 4

2.4.1 Multi-Output Allocation 4

2.4.2 End-of-Life Allocation 4

2.5 Cut-Off Criteria 5

2.6 Selection of LCIA Method and Types of Impacts 5

2.7 Interpretation to be Used 8

2.8 Data Quality Requirements 8

2.9 Assumptions and Limitations 8

2.10 Software and Database 9

2.11 Critical Review 9

3 Life-Cycle Inventory (LCI) Analysis 11

3.1 Data Collection 11

3.1.1 Data Collection and Quality Assessment Procedure 11

3.1.2 Fuels and Energy — Background Data 11

3.1.3 Raw Materials and Processes—Background Data 12

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3.1.4 Transportation 14

3.1.5 Emissions to Air, Water, and Soil 14

3.2 Isolation Gown System 14

3.2.1 Overview of Life Cycle 14

3.2.2 Raw Materials 15

3.2.3 Manufacturing 15

3.2.4 Transport 15

3.2.5 Use 15

3.2.6 End of Life 16

3.3 Wipers 17




3.3.4 Transport 18

3.3.5 Use 19


3.4 Napkins 22




3.4.4 Transport 23

3.4.5 Use 23


3.5 Life-Cycle Inventory Analysis Results 25

4 Life-Cycle Impact Assessment (LCIA) 29

4.1 Normalized Impact Assessment results 29

4.2 Detailed Impact Assessment Results 30

4.2.1 Isolation Gown 31

4.2.2 Wiper 33

4.2.3 Napkin 35

5 Interpretation 39

5.1 Identification of Relevant Findings 39

5.2 Data Quality Assessment 39

5.2.1 Precision and Completeness 39

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5.2.2 Consistency and Reproducibility 40

5.2.3 Representativeness 40

5.3 Completeness, Sensitivity, and Consistency 40

5.3.1 Completeness 40

5.3.2 Sensitivity Analysis on Single Parameters 40

5.3.3 Consistency 46

5.4 Conclusions, Limitations, and Recommendations 46

5.4.1 Conclusions 46

5.4.2 Limitations and Assumptions 47

5.4.3 Recommendations 47

6 References 48

Annex

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List of Figures

Page

Figure ES-1-1. Isolation gown GWP breakdown viii

Figure ES-1-2. Napkin GWP breakdown viii

Figure 3-1. System boundaries of fabric manufacturing LCI 13

Figure 3-2. Isolation gown wash chemistry (in %) 16

Figure 3-3. Wiper wash chemistry (in %) 20

Figure 3-4. Napkin wash chemistry (in %) 24

Figure 4-1. Normalized impacts for disposable isolation gown (worst case) 29

Figure 4-2. Example results graph 31

Figure 4-3. Isolation gown LCA results per 100 use cases 32

Figure 4-4. Isolation gown GWP breakdown 33

Figure 4-5. Wiper LCA results for 100 use cases 34

Figure 4-6. Wiper GWP breakdown 35

Figure 4-7. Napkin LCA results for 100 use cases 36

Figure 4-8. Napkin GWP breakdown 38

Figure 5-1. Disposable gown parameter sensitivity (GWP) 42

Figure 5-2. Reusable gown parameter sensitivity (GWP) 42

Figure 5-3. Disposable wiper parameter sensitivity (GWP) 44

Figure 5-4. Reusable wiper parameter sensitivity (GWP) 44

Figure 5-5. Disposable napkin parameter sensitivity (GWP) 45

Figure 5-6. Reusable napkin parameter sensitivity (GWP) 46

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List of Tables

Page

Table 2-1. Reference flows 2

Table 2-2. System boundaries 3

Table 2-3. TRACI impact assessment descriptions 7

Table 2-4. Other environmental indicators 7

Table 3-1. Key energy datasets used in inventory analysis 11

Table 3-2. Key material and process data sets used in inventory analysis 12

Table 3-3. Isolation gown parameters 17

Table 3-4. Isolation gown washing 17

Table 3-5. Wiper parameters 21

Table 3-6. Wiper washing 21

Table 3-7. Napkin parameters 25

Table 3-8. Napkin washing 25

Table 3-9. LCI results (kg of each material) for the isolation gown systems 26

Table 3-10. LCI results (kg of each material) for the wiper systems 27

Table 3-11. LCI results (kg of each material) for the napkin systems 28

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Executive Summary

The Textile Rental Services Association of America (TRSA) commissioned Exponent and PE

INTERNATIONAL, Inc., to compare selected reusable textiles against alternative disposable

products. Environmental performance was evaluated for three types of textile products. Because

the results of this comparison may be used for external communication, a critical review panel

was engaged to ensure that the study meets the requirements of the ISO 14044 standard.

The scope of the study includes raw materials, production, use, and disposal of three pairs of

reusable and disposable products: isolation gowns, wipers, and premium food-service napkins.

Primary data were collected from TRSA member companies, and data gaps were filled using

literature data and inventories from PE’s GaBi 2012 database. Because many parameters in the

life cycle of these products vary significantly, each system was modeled with worst-case

assumptions, best-case assumptions, and in certain cases, mid-high and mid-low assumptions.

Best-case assumptions are defined as those that lead to lowest environmental impacts, followed

by mid-low, then mid-high and worst-case.

One area displaying significant variability was the use-phase washing process. To address this

range, best-, mid-, and worst-case wash scenarios were created by ranking data providers within

a product group by total energy demand (natural gas + electricity).

Results were evaluated for different environmental impact categories: acidification potential

(AP), eutrophication potential (EP), global warming potential (GWP), ozone depletion potential

(ODP), primary energy demand (PED), and smog formation potential (Smog). Across all

categories considered, the disposables’ impacts are mostly linked to raw materials and

manufacturing. The reusable products’ primary impacts are driven mainly by use-phase washing

and manufacturing.

GWP impacts are shown below for isolation gowns, with burdens split across the different life-

cycle stages (Figure ES-1). The other impacts show similar results for isolation gowns;

reusables appear to have significantly less impact than their disposable alternatives.

Results for wipers are very similar and therefore are not displayed here; the worst-case reusables

appear to perform significantly better than the best-case disposables, with the exception of EP,

which is dominated by wastewater emissions during laundry.

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Figure ES-1-1. Isolation gown GWP breakdown

For napkins, the best- and worst-case scenarios overlap each other, depending on the

assumptions and data used (Figure ES-2). For example, disposable napkins come in a range of

weights and recycled content, which can cause the results to vary considerably. Additionally,

literature suggests quite a range of environmental impacts for the manufacturing of paper. The

comparison is evaluated based on scenarios wherein a consumer uses one napkin per meal.

Finally, laundry energy demand was a key variable for reusable napkins.

Figure ES-1-2. Napkin GWP breakdown

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The worst-case and mid-high disposable napkin scenarios appear to have considerably higher

impacts than all reusable scenarios. However, best-case and mid-low disposables are

comparable with or slightly lower in impact than the worst-case and mid-high reusable

scenarios.

Transportation and disposal are small contributors for all products and impacts considered.

In summary, the following conclusions appear to be reasonable:

Reusable isolation gowns have clear environmental benefit compared to the

analyzed disposable products, except in the case of ODP. The benefit comes

from raw materials weight differences and nonwovens manufacturing.

For wipers, the reusable products analyzed have a clear benefit for all impacts

except EP. The benefit comes from raw-material differences. For EP,

reusables have higher burdens, driven by wastewater emissions, which may

not be relevant for all facilities.

For napkins, worst and mid-high disposable scenarios appear to have higher

burden than all reusable scenarios. The mid-low and best case disposable

scenarios have similar but slightly lower impact than reusables. The product

weight has the greatest influence on results, followed by recycled content,

choice of high- or low-burden pulp, and use-phase washing variability.

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1 Goal of the Study

The Textile Rental Services Association (TRSA) represents companies that provide and launder

reusable textiles as a service to their clients. The goal of the study was to compare selected

reusable textiles against alternative disposable products. Environmental performance was

evaluated for the three case studies of reusable and disposable isolation gowns, wipers, and

napkins. The results of this comparison may be used for external communication, so a critical

review panel was engaged to ensure that the study meets the requirements of the ISO 14040/44

standards.

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2 Scope of the Study

The following section describes the general scope of the project to achieve the stated goals. This

includes identification of specific product systems to be assessed, their functional units, the

system boundary, allocation procedures, cut-off criteria, among others.

2.1 Product Systems to be Studied

The three case studies evaluate reusable and disposable isolation gowns, wipers, and napkins.

Isolation gowns are used in a healthcare setting to protect staff working in infectious conditions.

Reusable and disposable gowns provide equivalent levels of protection, but the reusable gowns

typically last for 64 washes. Wipers are used in industrial settings to clean oil, grease, and

solvents off of equipment. Reusable wipers typically last for 12 washes before they begin to

break down. Napkins are used in dining and hospitality to prevent stains and clean spills.

Reusable napkins typically last at least 100 washings.

2.2 Functional Unit and Reference Flows

TSRA desires to compare the environmental performance of the reusable textile products to that

of disposal products; therefore, the functional unit compares products on the basis of 100 use

cases. To provide a fair comparison, the reusables and disposable alternatives must perform the

same function, so the reference flows listed below were chosen (Table 2-1). Because the number

of lifetime uses is a variable quantity, the number of reusable products needed to provide 100

uses varies from the best-case to the worst-case scenario. The masses shown represent the total

weight of material needed to cover the range of best- and worst-case assumptions.

Table 2-1. Reference flows

Isolation Gown Wiper Napkin

Reusable 1.02–2.04 PET gowns [0.313−0.739 kg]

8.33 cotton towels [0.227–0.265 kg]

1 PET napkin [0.032–0.051 kg]

Disposable 100 PP gowns [14.5 kg–22.2 kg]

100 pulp & PET towels [0.98 kg]

100 premium paper napkins [0.57–2.35 kg]

The assumed lifetime uses of each product is an important factor to the overall comparison,

because manufacturing impacts are spread over the number of uses. Isolation gown lifetime

comes from a 1999 TRSA Textile Life Survey of healthcare barrier gowns. Based on 4 years of

data, the researchers found that the number of uses had a range of 98.08 (highest), 64.29

(median), and 49.13 (lowest). Wiper lifetime comes from a 1997 study “Environmental

Assessment of Shop Towel Usage in the Automotive and Printing Industries,” by the National

Risk Management Research Laboratory in the Office of Research and Development. The study

reported that woven towels have approximately 12 cycles of shop use and laundering at

industrial laundries. These ranges are reflected in best-, mid-, and worst-case scenarios for each

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product. Napkin life data comes from the University of Kentucky Textile Lab testing document.

Based on standard ASTM testing procedures, they found that napkins still perform after 100

uses. We assumed that napkins will be used until they fail; the University of Kentucky testing

has shown that they will last at least 100 uses, so that is the lifetime modeled in our study.

2.3 System Boundaries

The scope of the study includes production, use, and disposal of three pairs of reusable and

disposable products: isolation gowns, wipers, and premium food-service napkins. The analysis

includes raw material production through manufacturing, transport, use, and final disposal. The

geographic scope of the project is the United States.

Table 2-2 summarizes major components being considered for inclusion and exclusion from the

study and has been shaped by the need to accurately reflect the environmental burden associated

with the functional unit. While excluded parameters, such as packaging, may provide

refinements to the LCA, it was determined not to use parameters that are judged to have minor

impacts on the results of the LCA.

Table 2-2. System boundaries

Included Excluded

Raw materials production (forestry, chemicals, etc.)

Use of auxiliary materials, water, and energy during manufacturing, converting, and use

Emissions to air, water, and soil during manufacturing, converting, and use

Transport of raw materials and finished products

Disposal

Construction of capital equipment

Maintenance and operation of support equipment

Human labor and employee commute

Overhead (heating, lighting, warehousing) of manufacturing facilities

Internal transportation (within a manufacturing facility)

Packaging of products

2.3.1 Time Coverage

Primary data collected from TRSA member companies represent the year 2012. Secondary data

on product composition and manufacturing are taken from a range of sources between 1994 and

2013. Additional data necessary to model material production, energy use, etc., were adopted

from PE’s GaBi 2012 database and are described in further detail in Chapter 3.

2.3.2 Technology Coverage

Data on reusables’ material composition and manufacturing are primary data from TRSA

member companies, supplemented with secondary data from literature and the PE database.

Most disposables’ data come from secondary sources. In some cases, manufacturing details for a

given technology are unknown, so proxy data are used to represent best- and worst-case

scenarios. Table 3-2 gives more detail on the sources for the data used.

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2.3.3 Geographic Coverage

Data collected are representative of the United States, with the exceptions noted in Table 3-2.

2.4 Allocation

2.4.1 Multi-Output Allocation

Reusable wipers were made from scraps generated in another product system, so no burden has

been assigned to that product’s first life. Allocation was used in the GaBi background data, as

described below.

Allocation of upstream data (energy and materials):

For all refinery products, allocation is conducted by mass and net calorific

value. The manufacturing route of every refinery product is modeled, so the

effort expended in production of these products is calculated specifically.

Two allocation rules are applied:

1. The raw material (crude oil) consumption of the respective stages,

which is necessary for the production of a product or an intermediate

product, is allocated by energy (mass of the product calorific value

of the product)

2. The energy consumption (thermal energy, steam, electricity) of a

process (e.g., atmospheric distillation) being required by a product or

an intermediate product, are charged on the product according to the

share of the throughput of the stage (mass allocation).

Materials and chemicals needed during manufacturing are modeled using the

allocation rule most suitable for the respective product. For further

information on a specific product, see http://documentation.gabi-

software.com/.

2.4.2 End-of-Life Allocation

In cases where the materials are sent to landfills, the appropriate product-specific share of the

total EoL scrap is linked to a parameterized inventory that accounts for waste composition,

regional leakage rates, landfill gas capture, and utilization rates (flaring vs. power production).

A credit is assigned for power output using the regional grid mix.

TRSA and its members agree that products should be assumed to go to a landfill at their end of

life. Although incineration may be a possible path, the authors have decided to simply model all

waste in a landfill.

http://documentation.gabi-software.com/


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2.5 Cut-Off Criteria

No cut-off criteria were applied in this study. All reported data were incorporated and modeled

using best available LCI data. For use of proxy data, see Chapter 2.9.

2.6 Selection of LCIA Method and Types of Impacts

A set of impact assessment categories and other metrics considered to be of high relevance to

the goals of the project is shown in

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Table 2-3 and Table 2-4. The U.S. Environmental Protection Agency’s (EPA’s) TRACI 2.0

method was selected, because literature data for the production of virgin and recycled paper

reported impacts in TRACI 2.0.

Global warming potential (GWP) and primary energy demand (PED) were chosen because of

their relevance to climate change and energy efficiency, both of which are strongly interlinked,

of high public and institutional interest, and deemed to be among the most pressing

environmental issues of our times.

Eutrophication potential (EP), acidification potential (AP), and smog creation potential (Smog)

were chosen, because they are closely connected to air, soil, and water quality, and they capture

the environmental burden associated with commonly regulated emissions such as NOx, SO2,

VOCs, and others.

Ozone depletion potential (ODP) was chosen because of its high political relevance, which

eventually led to the worldwide ban of ozone-depleting substances. Current exceptions to this

ban include the application of ozone-depleting chemicals in nuclear power production. In

addition, the slash-and-burn cultivation of field crops is known to result in relevant emissions of

ozone-depleting substances. The indicator is therefore included for reasons of completeness and

to be able to gauge the relevance of these emissions in comparison to other impacts.

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Table 2-3. TRACI impact assessment descriptions

Impact Category Description Unit Reference

Acidification potential (AP)

A measure of emissions that cause acidifying effects to the environment. The acidification potential is assigned by relating the existing S-, N-, and halogen atoms to the molecular weight.

kg SO2 equivalent (Bare 2011; U.S. EPA 2012)

Eutrophication potential (EP)

A measure of emissions that cause nutrifying effects to the environment. The eutrophication potential is a stoichiometric procedure, which identifies the equivalence between N and P for both terrestrial and aquatic systems

kg Nitrogen equivalent (Bare 2011; U.S. EPA 2012)

Global warming potential (GWP)

A measure of greenhouse gas emissions, such as CO2 and methane. These emissions are causing an increase in the absorption of radiation emitted by the earth, magnifying the natural greenhouse effect.

kg CO2 equivalent (Bare 2011; U.S. EPA 2012)

Ozone depletion potential (ODP)

A measure of air emissions that contribute to the depletion of the stratospheric ozone layer. Depletion of the ozone to leads to higher levels of UVB ultraviolet rays.

kg CFC-11 equivalent (Bare 2011; U.S. EPA 2012)

Smog creation potential (Smog)

A measure of emissions of precursors that contribute to low level smog, produced by the reaction of nitrogen oxides and VOC’s under the influence of UV light.

kg O3 equivalent (Bare 2011; U.S. EPA 2012)

Table 2-4. Other environmental indicators

Indicator Description Unit Reference

Primary energy demand (PED)

A measure of the total amount of fossil resources extracted from the earth. PED is expressed in energy demand from non-renewable resources (e.g., petroleum, natural gas, etc.).

MJ (surplus)

(Bare 2011; U.S. EPA 2012)

It shall be noted that the above impact categories represent impact potentials; i.e., they are

approximations of environmental impacts that could occur if the emitted molecules would

(a) actually follow the underlying impact pathway and (b) meet certain conditions in the

receiving environment while doing so. In addition, the reported emissions represent only that

fraction of the total environmental load that corresponds to the functional unit.

LCIA results are therefore relative expressions only and do not predict actual impacts, the

exceeding of thresholds, safety margins, or risks.

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2.7 Interpretation to be Used

The study applies normalization to statistical yearly U.S. emissions as a means to establish the

order of magnitude in which each product system would contribute to the average

environmental burden of a given year. This is a comparative assertion to be disclosed to third

parties, so no grouping or quantitative cross-category weighting has been applied. Instead, each

impact is discussed in isolation, without reference to other impact categories, before final

conclusions and recommendations are made.

Note that, in situations where no product outperforms all of its alternatives in each of the impact

categories, some implicit form of cross-category evaluation is inevitable to draw conclusions

regarding the environmental superiority of one product over the other. ISO 14044 rules out the

use of quantitative weighting factors in comparative assertions to be disclosed to the public, so

this evaluation will take place qualitatively, and the defensibility of the results therefore depends

on the authors’ expertise and ability to convey the underlying line of reasoning that led to the

final conclusion.

2.8 Data Quality Requirements

The data used to create the inventory model shall be as precise, complete, consistent, and

representative as possible with regard to the goal and scope of the study under given time and

budget constraints.

Measured primary data are considered to be of high precision, followed by

calculated and estimated data.

Completeness is judged based on the completeness of the inputs and outputs per

unit process and the completeness of the unit processes themselves. As stated in

Section 2.4.2, no cut-off criteria were applied.

Consistency refers to modeling choices and data sources. The goal is to ensure

that differences in results occur due to actual differences between product

systems, and not due to inconsistencies in modeling choices, data sources,

emission factors, or other factors.

Representativeness expresses the degree to which the data match the geographic,

temporal, and technological requirements defined in the study’s goal and scope.

An evaluation of the data quality with regard to these requirements is provided in the

interpretation chapter of this report.

2.9 Assumptions and Limitations

A number of assumptions are used where adequate data were not available from either primary

or secondary sources—in most cases, a range of values was used to signify “best-case” and

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“worst-case” scenarios. Notable assumptions and limitations are described below, and a full list

of data used is included in Chapter 3 below.

Manufacturing of disposable isolation gowns is modeled based on data for

surgical gowns (worst case) or spunbond nonwoven fabric (best case).

Initial transportation distance from manufacturing to customer was assumed

to be 250 miles (worst case) or 100 miles (best case) for all disposable and

reusable product scenarios. Although some of these products typically may

be manufactured overseas, this comparison focuses on North American

boundary conditions. The environmental implications of this choice are

small, because ocean transport has considerably lower impact than trucking.

For example, the global warming effect of transporting a good 100 miles by

truck is roughly equivalent to shipping that same item 3,300 miles by ship.

Cotton scraps used in reusable wiper manufacturing were assumed to carry

no fraction of the burden of virgin cotton fiber. The scraps are generated as

internal waste (part of another product system), rather than purchased on the

scrap market, so they were given no environmental burden.

Consumers were assumed to use one premium disposable napkin or one cloth

reusable napkin per meal regardless of product weight. Disposable napkin

weights were taken from publically available information on premium, two-

ply napkins with varying weights and levels of recycled content.

Without data on the weights and manufacturing of elastomeric cuffs and

other isolation gown trim, they have been excluded from the study.

Despite uncertainty around which scenarios are more prevalent in real-life situations, results are

interpreted for all scenarios to provide additional confidence in the conclusions.

2.10 Software and Database

The LCA model was created using the GaBi 6 software system for life-cycle engineering,

developed by PE INTERNATIONAL AG. The GaBi 2012 LCI database provides the life-cycle

inventory data for the background system, as shown in Chapter 3.

2.11 Critical Review

TRSA intends to disclose the LCA results to the public in external or business-to-customer

communications; therefore, ISO14040 requires third-party review by a panel of three

independent experts. The reviewers were:

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Dr. Arpad Horvath, Consultant, Berkeley, California (panel chair)

Jim Mellentine, Sustainable Solutions

Dr. Christopher Pastore, Philadelphia University.

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3 Life-Cycle Inventory (LCI) Analysis

3.1 Data Collection

3.1.1 Data Collection and Quality Assessment Procedure

All primary data were collected by email, with the respective data providers in the participating

companies using pre-formatted spreadsheets. Data were cross-checked for completeness and

plausibility using mass balance, stoichiometry, and benchmarking. If gaps, outliers, or other

inconsistencies occurred, PE INTERNATIONAL engaged with the data provider to resolve any

open issues.

The project was further subjected to a comprehensive quality assurance process at every major

milestone in the project, to analyze and ensure model integrity, data accounting, and consistency

with the goal and scope.

Product composition and manufacturing details were collected from TRSA member companies

when possible, but their main role was to provide washing details. Data on washing energy and

water came from a Clean Green survey of 70 TRSA member companies. Chemistry and

emissions data were reported by 21 sites.

Many parameters in the life cycle of these products had significant variability, so each system

was modeled with worst-case assumptions, best-case assumptions, and in certain cases, mid-

level or mid-high and mid-low assumptions. In general, best-case assumptions are defined as

those that lead to lower environmental impacts, and worst-case assumptions lead to higher

environmental impacts. The mid-high scenario has higher impacts than mid-low, which has

higher impacts than the best case. By using these scenarios to model the disposable and reusable

product systems, uncertainty due to assumptions and data variability was accounted for, which

allows conclusions to be drawn with more confidence.

3.1.2 Fuels and Energy — Background Data

National and regional averages for fuel inputs and electricity grid mixes were obtained from the

GaBi 6 database 2012. Table 3-1 shows the most relevant LCI data sets used in modeling the

product systems.

Table 3-1. Key energy datasets used in inventory analysis

Energy Data Set Name Primary Source Year Geography

Electricity Electricity grid mix PE 2009 US

Technical heat Thermal energy from natural gas PE 2009 US

Diesel for trucking Diesel mix at refinery PE 2009 US

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Documentation for all generic data sets can be found at http://www.gabi-

software.com/support/gabi/gabi-6-lci-documentation/.

3.1.3 Raw Materials and Processes—Background Data

Data for up- and downstream raw materials and unit processes were obtained from the GaBi 6

database 2012. Table 3-2 shows the most relevant LCI data sets used in modeling the product

systems. Documentation for all generic datasets can be found at http://www.gabi-

software.com/support/gabi/gabi-6-lci-documentation/.

Note that, in some cases, a material or process is used in multiple product systems. For ease of

display, the Reusable scenarios are abbreviated (R), and Disposable scenarios are abbreviated

(D).

Table 3-2. Key material and process data sets used in inventory analysis

Product System(s) Material/Process Data Set Name Primary Source Year Geography

Gown (R) Napkin (R) Wiper (D)

PET fiber Polyethylene terephthalate fibers (PET)

PE 2011 US

Gown (D) PP fiber Polypropylene fibers (PP)

PE 2011 US

Gown (R) Wiper (R) Fabric manufacturing

Woven cotton fabric manufacturing

Cotton Inc. 2011 Global

Napkin (D) Wiper (D) Pulp Virgin Pulp

Deinked Pulp

Environ

Environ

2013

2013

North America

Napkin (D) Wiper (D) Tissue making Tissue making EC Joint Research Center

2011 EU

Wiper (R) Recycled cotton n/a n/a n/a n/a

Data for woven cotton fabric manufacturing comes from a high-quality LCI recently published

by Cotton, Inc. The global average data set is based on data from China, India, Latin America,

and Turkey, representing 66% of global production. The following processes are used to create

woven fabric from fiber and give it desired properties such as color, texture, and finishes: beam

/ slash / dry, weaving, continuous dyeing, finishing, and sanforizing. System boundaries are

shown in Figure 3-1. Energy, chemicals, and transport are included. Manufacturing synthetics is

assumed to be comparable to cotton, so this LCI is an appropriate proxy.

http://www.gabi-software.com/support/gabi/gabi-6-lci-documentation/




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Figure 3-1. System boundaries of fabric manufacturing LCI

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3.1.4 Transportation

The GaBi data sets for road transport and fuels were used to model transportation. Truck

transportation within the United States was modeled using the GaBi 6 US truck transportation

data sets. The vehicle types, fuel usage, and emissions for these transportation processes were

developed using a GaBi model based on the U.S. Census Bureau Vehicle Inventory and Use

Survey (2002) and U.S. EPA emissions standards for heavy trucks in 2007. The 2002 VIUS

survey is the latest available survey describing truck-fleet fuel consumption and utilization

ratios in the U.S., and the 2007 EPA emissions standards are considered to be the most

appropriate data available for describing current U.S. truck emissions.

3.1.5 Emissions to Air, Water, and Soil

Emission data for all upstream materials, electricity, and energy carriers were obtained from the

GaBi 6 database 2012. The emissions (CO2, NOx, SO2, etc.) due to the use of electricity and

combustion of fuels are accounted for with the use of the database processes.

Primary data on water emissions from laundering were obtained from selected laundry facilities.

Lacking enough consistent information for an industry average, best- and worst-case emissions

data from selected laundries were used.

Emissions associated with transportation were determined by capturing the logistical operations

of involved companies (data collected from the companies for the reference year). Energy use

and the associated emissions were calculated using pre-configured transportation models from

the GaBi 6 database 2012, adapted with transportation supplier data (specific fuel economy,

specific emissions, etc.).

3.2 Isolation Gown System

3.2.1 Overview of Life Cycle

Isolation gowns are used in the healthcare industry to protect staff working in infectious

conditions. Reusable gowns are made from woven polyester fabric. Disposable gowns are made

from nonwoven polypropylene fabric. Both products are manufactured, then delivered by truck.

Reusable products are picked up from TRSA’s clients, then laundered and returned. After their

useful lives, both products are disposed of in a standard landfill.

Isolation gown lifetime comes from a 1999 TRSA Textile Life Survey of healthcare barrier

gowns. Based on 4 years of data, they found that the number of uses ranged from 98.08

(highest), to 64.29 (median), to 49.13 (lowest). To achieve the reference flow of 100 uses, the

reusable gowns must be produced 1.02, 1.56, and 2.04 times, respectively.

Data points used in each scenario are summarized in Table 3-3.

1200473.000 - 8193 15

3.2.2 Raw Materials

Primary data were collected on raw materials from a TRSA member, in the case of reusables.

The disposable gown material type and composition were taken from literature (McIlvane,

2009).

3.2.3 Manufacturing

For the reusable gown, a global average data set for woven fabric manufacturing based on data

from (Cotton, Inc., 2012) was used. This data set includes fiber preparation and the processes to

give it desired properties such as color, texture, and finishes.

For disposable gown manufacture, we considered the production of a non-woven polypropylene

gown. Our worst-case scenario included electricity (5.16 MJ/gown) for surgical gown

manufacturing (McIlvane, 2009). Our best-case scenario included electricity (1.31 MJ/gown) for

spunbond nonwoven production (Malkan, 1994). The spunbond nonwoven energy data for this

best-case scenario was also used for reusable wipers.

Primary data on manufacturing waste were used for all disposables and reusables scenarios

(5.7% and 5.0%, respectively). All inputs upstream of waste are increased to account for these

losses.

Note that isolation gowns likely have elastomeric cuffs, pockets, and other trim. Without data on

the weights and manufacturing of these trim, they have been excluded from the study.

3.2.4 Transport

For the transport of raw materials to manufacturing facilities, an assumed transportation distance

of 100 miles by a Class 5 truck is included. For the first delivery of finished products to

customers, no transportation data were collected. Lacking data, we assumed either 100 miles

(best case) or 250 miles (worst case) for both reusables and disposables.

Because reusables are delivered to clients and then picked up for laundering, we collected data

on average delivery and pickup routes among TRSA members. The average total distance for a

route was 110 miles for wipers and 70 miles for gowns and napkins. Textiles are not very dense,

so delivery vans will meet their volumetric capacity before approaching their weight capacity.

Truck emissions are calculated based on the payload weight as a fraction of total capacity,

known as the truck’s utilization, so primary data on laundry density and truck volume were

needed. The primary data from TRSA member companies had considerable variability, so a

range of utilization factors was used (worst, 0.14; mid-high, 0.24; mid-low, 0.4; and best, 0.61).

3.2.5 Use

Primary data were collected from the TRSA to quantify the energy, water, and chemicals

needed for laundering reusable textiles. Laundry data were provided for general industrial-scale

washing, as well as for gowns alone. The following table shows inputs and outputs of the

laundry process for each scenario. Use-phase scenarios are divided into worst, mid-high, mid-

1200473.000 - 8193 16

low, and best case. In cases where detail was unavailable for all the inputs and outputs

(e.g., wash chemistry), we applied values averaged from all other respondents.

A summary of inputs and outputs from the washing process is presented in Table 3-4.

The wash chemistry is made from a mixture of chemicals (Figure 3-2). We collected primary

data from three member companies on the composition of this mixture. LCI data for these

chemicals were taken from the GaBi 2012 database.

Figure 3-2. Isolation gown wash chemistry (in %)

3.2.6 End of Life

At the end of their useful life, we assume that the products are trucked 20 miles to a standard

landfill. PE’s GaBi database includes the fuel and emissions for landfill earth movers, leachate

to water, and emissions air. As described in Section 2.4.2, the capture and flaring of landfill gas

is also included based on prevalence across U.S. landfills.

A summary of data points used in each scenario is given below. Text in bold denotes parameters

that vary across the different scenarios.

1200473.000 - 8193 17

Table 3-3. Isolation gown parameters

Gown Scenario Raw Materials Manufacturing Transport Use End of

Life

Disposables Worst Case 7.83 oz. PP

produced 100 times

Surgical gown

manuf. energy (5.16 mj)

250 mi delivery, 0.14 utilization

n/a standard landfill

Best Case 5.12 oz. PP

produced 100 times

Spunbond nonwoven energy (1.31 mj)



Reusables Worst Case 12.8 oz. PET

replaced 2.04 times Average weaving, 0.22 mj cut & sew

70 mi pickup / delivery, 0.14

utilization

worst

washing standard landfill

Mid – High 12.8 oz. PET

replaced 1.56 times Average weaving, 0.22 mj cut & sew


utilization

mid-high


Mid – Low 10.82 oz. PET

replaced 1.56 times Average weaving, 0.007 mj cut &

sew


utilization

mid-low


Best Case 10.82 oz. PET

replaced 1.02 times Average weaving, 0.007 mj cut &

sew


utilization

best


A summary of inputs and outputs from the washing process is given below.

Table 3-4. Isolation gown washing

Gown Worst Mid-High Mid-Low Best

Electricity [Btu / lb laundry] 614.16 375.32 375.32 272.96

Natural Gas [Btu / lb laundry] 3471.00 2185.00 2185.00 1638.00

Water [gal / lb laundry] 2.23 1.25 1.25 0.78

Wash Chemistry [lbs / lb laundry] 0.01 0.01 0.00 0.01

Waste Water [gal / lb laundry] 1.60 1.58 1.45 1.48

3.3 Wipers


Wipers are used in industrial settings to clean oil, grease, and solvents off equipment. Reusable

wipers are made from recycled cotton fibers. Disposable wipers are made from nonwoven pulp

and polyester fabric. Both products are manufactured and then are assumed to be delivered by

truck. Reusable products are picked up from TRSA’s clients using a Class 5 truck (step van),

then laundered and returned. After their useful lives, both products are disposed of in a standard

landfill.

1200473.000 - 8193 18

Wiper lifetime comes from a 1997 EPA study, “Environmental Assessment of Shop Towel

Usage in the Automotive and Printing Industries,” by the National Risk Management Research

Laboratory in the Office of Research and Development. The study reported that woven towels

have approximately 12 cycles of shop use and are laundered via water washing at industrial

laundries.

A summary of data points used in each scenario is presented in Table 3-5.

3.3.2 Raw Materials

Primary data were collected on raw-material weights from TRSA members. The product is

made primarily from cotton scraps that are reclaimed from the manufacturing site. Because the

scraps aren’t purchased from external sources, no burden from the virgin production of cotton is

allocated to the material.

The disposable wiper material type and composition were taken from literature (Pullman, 1997).

Data for kraft pulp production also came from literature (Joint Research Centre, 2012), but the

source documented a significantly wide variation in the technologies used for kraft pulp making

and subsequent tissue manufacturing. Ranges were provided to represent the current industry

practice, so we built “high-impact” and “low-impact” versions of kraft pulp and tissue making

for use in the model.

Some disposable wipers may also contain recycled content. A TRSA member who manufactures

disposable wipers provided the information that wipers can contain as much as 40% post-

consumer recycled material. He states that the recycled content likely comes from the paper

rather than polyester. To consider this aspect, we took the formulation specified in literature

(65% pulp / 35% PET) and assumed that the best-case wiper had 40% recycled pulp / 15%

virgin pulp / 35% PET. The worst-case scenario was made with 65% virgin pulp / 35% PET.

3.3.3 Manufacturing

Lacking primary data on the manufacturing of reusables, we assumed energy demand to match

the generic spunbond nonwoven process (0.286 MJ/towel). The spunbond nonwoven energy

data for wipers were the best data available and were also used for disposable gowns. Primary

data came from TRSA member companies on water (0.02 L/towel), as well as waste (8% and

10% for best and worst cases, respectively). All inputs upstream of waste are increased to

account for these losses.

Disposable wiper manufacturing energy and water use were taken from literature (Pullman,

1997).

3.3.4 Transport

For the transport of the raw materials to manufacturing facilities, an assumed transportation

distance of 100 miles by truck is included. For the first delivery of finished products to



1200473.000 - 8193 19

Reusables are delivered to clients, then picked up for laundering, so we collected data on

average delivery / pickup routes among TRSA members. The average total distance for a route

was 110 miles for wipers and 70 miles for gowns and napkins. Because textiles are not very

dense, delivery vans will meet their volumetric capacity before approaching their weight

capacity. Truck emissions are calculated based on the payload weight as a fraction of total

capacity, known as the truck’s utilization, so primary data on laundry density and truck volume

were needed. The primary data from TRSA member companies had considerable variability, so

a range of utilization factors was used (worst, 0.14; mid-high, 0.24; mid-low, 0.4; and best,

0.61).

3.3.5 Use



washing, as well as for wipers alone. The following table shows inputs and outputs of the




A summary of inputs and outputs from the washing process is presented in

Table 3-6.

The wash chemistry is made from a mixture of chemicals (Figure 3-3). We collected primary


chemicals come from the GaBi 2012 database.

1200473.000 - 8193 20

Figure 3-3. Wiper wash chemistry (in %)

3.3.6 End of Life

At the end of their useful life (one use for disposables or 12 uses for reusables), the products are

trucked 20 miles to a standard landfill. PE’s GaBi database includes the fuel and emissions for

landfill earth movers, leachate to water, and emissions to air. As described in Section 2.4.2, the

capture and flaring of landfill gas is also included, based on prevalence across U.S. landfills.

The parameters used in each scenario are given below. Text in bold denotes parameters that

vary across the different scenarios.

1200473.000 - 8193 21

Table 3-5. Wiper parameters

Wiper Scenario Raw Materials Manufacturing Transport Use End of Life

Disposables Worst Case

0.35 oz virgin Pulp (high impact) & PET produced 100 times

wiper manufacturing

(literature)



Best Case

0.35 oz recycled and virgin Pulp (low impact) &

PET produced 100 times

wiper manufacturing

(literature)



Reusables Worst Case

1.12 oz scraps replaced 8.33 times

spunbond nonwoven process


utilization

worst washing

standard landfill

Mid - High

1.02 oz scraps replaced

8.33 times

spunbond nonwoven process


utilization

mid-high


Mid - Low


wiper manufacturing

(literature)


utilization

mid-low washing

standard landfill

Best Case


wiper manufacturing

(literature)

110 mi pickup / delivery, 0.61 utilization

best washing

standard landfill

Inputs and outputs from the washing process are given below.

Table 3-6. Wiper washing

Wiper Worst Mid-High Mid-Low Best


Natural gas [Btu / lb laundry] 3542.00 2024.00 2024.00 1159.00


Wash chemistry [lbs / lb laundry] 0.01 0.04 0.05 0.03

Waste water [gal / lb laundry] 3.57 3.16 1.45 0.79

Sludge [lbs / lb laundry] 0.00 3.50 1.70 1.60

Grease [mg / L wastewater] 750.00 750.00 750.00 750.00

Solvents [mg / L wastewater] 50.00 50.00 50.00 50.00

Heavy metals [mg / L wastewater] 6.00 6.00 6.00 6.00

Biological oxygen demand

[mg / L wastewater] 750.00 750.00 750.00 750.00

Total suspended solids

[mg / L wastewater] 750.00 750.00 750.00 750.00

Sodium hydroxide [mg / L wastewater] 0.21 0.21 0.21 0.21

Detergent [mg / L wastewater] 0.10 0.10 0.10 0.10

Softener/souring agent

[mg / L wastewater] 0.13 0.13 0.13 0.13

1200473.000 - 8193 22

3.4 Napkins


Napkins are used in dining and hospitality to prevent stains and clean spills. We are evaluating

reusable napkins made from polyester. Disposable napkins are made from paper tissue derived

from virgin and recycled pulp. Both products are manufactured then delivered by truck.

Reusable products are picked up from TRSA’s clients, then laundered and returned. After their

useful lives, both products are disposed in a standard landfill.

Napkin life data come from the University of Kentucky Textile Lab testing document

(Meredith, 2011). Based on standard ASTM testing procedures, they found that napkins still

perform after 100 uses.

Parameters used in each scenario are presented in Table 3-7.

3.4.2 Raw Materials

Primary data were collected on raw material weights from TRSA members in the case of

reusables.

The disposable-napkin data for paper production came from literature (Environ, 2012) (Joint

Research Centre, 2012). The Environ report included some discussion about the potential range

in impacts for pulp making, depending on variations in pulp production energy, pulp production

fuel mix, and assumptions regarding recycling allocation. Despite the range of possible impacts

that pulp could have, we reduced the number of disposable napkin scenarios by considering only

the baseline pulp making for use in this study. Further justification for this decision is included

in Section 4.2.3. The Environ report describes only the production of pulp-making, but not

paper making, so data from the Joint Research Centre was used for paper making.

The Joint Research Centre study documented a significantly wide variation in the technologies

used for tissue manufacturing. Because ranges were presented to represent the current industry

practice, we built “high-impact” and “low-impact” versions of tissue making for use in the

model.

Lacking industry data describing the range of products available on the market, disposable-

napkin weights were taken from publically available information on premium, two-ply napkins

with varying weights and levels of recycled content. The worst-case scenarios are represented

by a 23.5-gram 100% virgin napkin made by Dunicel, as reported in an existing LCA (IVL,

2011). The mid-high napkin was represented by the Georgia Pacific Preference napkin (GP

Preference, 2013), a 5.4-gram 30% recycled product. The mid-low napkin was represented by

the Georgia Pacific Essentials napkin (GP Essentials, 2013), a 10.2-gram 100% virgin product.

The best-case scenarios are represented by a 5.7-gram 100% recycled napkin made by Earth

First (Earth First, 2013).

1200473.000 - 8193 23

3.4.3 Manufacturing

For the reusable napkin, we used a global average data set from the PE database for woven

fabric manufacturing. This data set includes fiber preparation and the processes to give it desired

properties such as color, texture, and finishes. Energy and waste for cut-and-sew are also

included in reusable napkin manufacturing. Primary data from two TRSA members showed

considerable differences, so they were used as best (0.02 MJ/napkin) and worst cases

(0.22 MJ/napkin).

The kraft pulp and tissue-making data from literature included manufacturing inputs and outputs

relevant to disposable napkins.

3.4.4 Transport

For the transport of the raw materials to manufacturing facilities, an assumed transportation

distance of 100 miles, by truck, is included. For the first delivery of finished products to



Reusables are delivered to clients then picked up for laundering; therefore, we collected data on

average delivery and pickup routes among TRSA members. The average total distance for a

route was 110 miles for wipers and 70 miles for gowns and napkins. Because textiles are not

very dense, delivery vans will meet their volumetric capacity before approaching their weight

capacity. Truck emissions are calculated based on the payload weight as a fraction of total

capacity, known as the truck’s utilization, so primary data on laundry density and truck volume

were needed. The primary data from TRSA member companies had considerable variability, so

a range of utilization factors was used (worst, 0.14; mid-high, 0.24; mid-low, 0.4; and best:

0.61).

3.4.5 Use



washing, as well as for napkins alone. The following table shows inputs and outputs of the




Inputs and outputs from the washing process are presented in Table 3-8.

The wash mixture is made from a combination of chemicals (Figure 3-4). We collected primary


chemicals come from the GaBi 2012 database.

1200473.000 - 8193 24

Figure 3-4. Napkin wash chemistry (in %)

3.4.6 End of Life

At the end of their useful life (one use for disposables or 100 uses for reusables), these napkins

are trucked 20 miles to a standard landfill. PE’s GaBi database includes the fuel and emissions

for landfill earth movers, leachate to water, and emissions to air. As described in Section 2.4.2,

the capture and flaring of landfill gas is also included based on prevalence across U.S. landfills.

The parameters used in each scenario are given below. Text in bold denotes parameters that

vary across the different scenarios.

1200473.000 - 8193 25

Table 3-7. Napkin parameters

Wiper Scenario Raw Materials Manufacturing Transport Use End of Life

Disposables Worst Case 23.5 g paper

produced 100 times

Virgin pulp + High-

impact papermaking, 0% recycled



Mid - High 10.2 g paper

produced 100 times

Virgin pulp + High-




Mid - Low 5.35 g paper

produced 100 times

Virgin pulp + Low-




Best Case 5.66 g paper

produced 100 times

Recycled pulp + Low-




Reusables Worst Case 50.8 g PET used 100 times

0.22 MJ/napkin, 1.5% waste


worst washing

standard landfill

Mid - High 50.8 g PET used 100 times



mid-high washing

standard landfill

Mid - Low 32.1 g PET used

100 times



mid-low washing

standard landfill

Best Case 32.1 g PET used

100 times



best washing

standard landfill

Inputs and outputs from the washing process are given below.

Table 3-8. Napkin washing

Wiper Worst Mid-High Mid-Low Best


Natural gas [Btu / lb laundry] 3471.00 2185.00 2185.00 1638.00


Wash chemistry [lbs / lb laundry] 0.01 0.01 0.00 0.01

Waste water [gal / lb laundry] 1.60 1.58 1.45 1.48

Sodium hydroxide [mg / L wastewater] 0.79 0.79 0.79 0.79

Detergent [mg / L wastewater] 0.87 0.87 0.87 0.87

Softener/souring agent [mg / L wastewater] 0.07 0.07 0.07 0.07

Mildewcide [mg / L wastewater] 0.04 0.04 0.04 0.04

3.5 Life-Cycle Inventory Analysis Results

ISO 14044 defines the Life Cycle Inventory Analysis Result as the “outcome of a life cycle

inventory analysis that catalogues the flows crossing the system boundary and provides the

starting point for life cycle impact assessment.” The complete inventory comprises hundreds of

flows, so the below table displays only a selection of flows, based on their relevance to the

1200473.000 - 8193 26

subsequent impact assessment, in order to provide a transparent link between the inventory and

impact assessment results.

The complete inventory is available on request from the study authors.

Table 3-9. LCI results (kg of each material) for the isolation gown systems

Type Flow Disposable

(Worst) Disposable

(Best) Reusable (Worst)

Reusable (Mid−High)

Reusable (Mid−Low)

Reusable (Best)

Resources

Crude oil 17.74287 9.650646 1.620897 1.14735 0.894749 0.596018

Hard coal 29.65383 9.002327 4.906118 3.603784 2.957338 1.907622

Lignite 6.449989 3.03078 1.361297 0.990311 0.814741 0.531038

Natural gas 35.16405 19.96574 10.02809 7.164633 5.955812 3.923817

Uranium 0.00078 0.000253 9.36E-05 6.78E-05 5.52E-05 3.54E-05

Emissions to Air

Carbon dioxide 153.6933 61.15521 41.24934 29.6622 24.47632 15.99842

Carbon monoxide 0.101645 0.039194 0.022535 0.015831 0.012 0.008239

Nitrogen dioxide 2.12E-05 8.86E-06 1.92E-05 1.29E-05 1.05E-05 6.67E-06

Nitrogen oxides 0.000174 8.28E-05 0.000175 0.00011 8.79E-05 5.61E-05

Sulphur hexafluoride 1.51E-10 4.48E-11 2.44E-11 1.76E-11 1.44E-11 9.26E-12

Dust (PM2.5−PM10) 0.012299 0.007615 0.003107 0.002168 0.001717 0.001031

Emissions to Water

Ammonia 0.000254 8.38E-05 0.000552 0.000419 0.000353 0.000231

Nitrate 0.009385 0.003587 0.009073 0.005458 0.004344 0.002731

Phosphorus 0.000421 0.000272 0.00091 0.000527 0.000417 0.00026

1200473.000 - 8193 27

Table 3-10. LCI results (kg of each material) for the wiper systems


(Worst) Disposable

(Best) Reusable (Worst)



Reusable (Best)

Resources

Crude oil 0.505965 0.364091 0.096692 0.058579 0.041688 0.027592

Hard coal 0.442995 0.394657 0.368757 0.261062 0.259283 0.197026

Lignite 0.245682 0.23964 0.059558 0.040506 0.03988 0.028158

Natural gas 0.82535 0.819847 0.796313 0.465872 0.457326 0.267812

Uranium 1.40E-05 1.27E-05 9.12E-06 6.46E-06 6.41E-06 4.88E-06

Emissions to Air

Carbon dioxide 7.470858 4.637717 3.207994 2.000259 1.93289 1.257854

Carbon monoxide 0.011657 0.006836 0.002181 0.00145 0.001288 0.000948

Nitrogen dioxide 0.001346 0.000298 1.00E-06 5.55E-07 5.29E-07 2.93E-07

Nitrogen oxides 1.89E-05 1.43E-05 1.24E-05 9.53E-06 9.62E-06 4.98E-06

Sulphur hexafluoride 2.12E-12 1.86E-12 2.07E-12 1.44E-12 1.43E-12 1.07E-12

Dust (PM2.5−PM10) 0.000767 0.000589 0.000243 0.000172 0.000165 0.000128

Emissions to Water

Ammonia 6.48E-06 8.80E-06 3.49E-06 2.37E-06 2.34E-06 1.71E-06

Nitrate 0.001646 0.000829 0.000772 0.000517 0.000506 0.000265

Phosphorus 8.87E-05 1.55E-05 9.08E-05 5.24E-05 4.92E-05 2.99E-05

1200473.000 - 8193 28

Table 3-11. LCI results (kg of each material) for the napkin systems


(Worst)

Disposable (Mid−High)

Disposable (Mid−Low)

Disposable (Best)

Reusable (Worst)



Reusable (Best)

Resources

Crude oil 0.498985 0.165358 0.017408 0.015198 0.147737 0.12197 0.074116 0.062826

Hard coal 0.031565 0.012838 0.035356 0.037381 0.5524028 0.437773 0.270805 0.203645

Lignite 0.036491 0.015617 0.00719 0.007603 0.1362179 0.112027 0.069142 0.056105

Natural gas 0.290342 0.121954 0.018278 0.01913 1.2865901 0.941588 0.593181 0.412984

Uranium 0.000224 9.67E-05 1.39E-05 1.47E-05 7.40E-05 5.59E-05 3.41E-05 2.46E-05

Emissions to Air 1.69E-07 5.42E-08 9.00E-07 9.52E-07 1.18E-05 9.00E-06 5.54E-06

Carbon dioxide 5.947407 2.435907 0.290152 0.298647 4.9998296 3.767585 2.353802 1.695704

Carbon monoxide 0.061234 0.026043 0.002245 0.00235 0.0025153 0.001888 0.001159 0.000841

Nitrogen dioxide 2.09E-07 8.95E-08 3.56E-08 3.77E-08 2.39E-06 1.75E-06 1.05E-06 6.99E-07

Nitrogen oxides 0.000121 5.21E-05 1.98E-06 2.10E-06 3.20E-05 2.40E-05 1.52E-05 1.33E-05

Sulphur hexafluoride 7.33E-13 3.12E-13 2.33E-13 2.46E-13 2.98E-12 2.29E-12 1.40E-12 1.01E-12

Dust (PM2.5–PM10) 0.001916 0.000825 0.000235 0.000249 0.0003217 0.000237 0.00015 0.000101

Emissions to Water 1.35E-06 5.71E-07 3.12E-07 3.30E-07 3.91E-05 3.78E-05 2.37E-05

Ammonia 0.011935 0.005142 0.000216 0.000227 1.65E-03 0.001148 0.000697 0.000493

Nitrate 3.63E-05 1.57E-05 5.65E-06 5.99E-06 1.56E-04 0.000101 5.81E-05 2.85E-05

Phosphorus 0.498985 0.165358 0.017408 0.015198 0.147737 0.12197 0.074116 0.062826

1200473.000 - 8193 29

4 Life-Cycle Impact Assessment (LCIA)

As mentioned, the reported impact categories represent impact potentials; i.e., they are

approximations of environmental impacts that could occur if the emitted molecules would (a)

follow the underlying impact pathway and (b) meet certain conditions in the receiving

environment while doing so. In addition, the reported emissions represent only that fraction of

the total environmental load that corresponds to the functional unit.

LCIA results are therefore relative expressions only and do not predict actual impacts, the

exceeding of thresholds, safety margins, or risks.

4.1 Normalized Impact Assessment results

The study applies normalization to statistical annual U.S. emissions as a means to establish the

order of magnitude with which each product system would contribute to the average per-capita

environmental burden of a given year. In Figure 4-1, the results are shown for an exemplar

scenario (worst-case disposable isolation gown), to provide some context on the relative

magnitude of the different impact categories considered. Because each impact is divided by the

respective U.S. per-capita burden, the normalized results are dimensionless. Normalization

factors are referenced in Section 0.

Figure 4-1. Normalized impacts for disposable isolation gown (worst case)

AP, EP, GWP, and smog creation potential are in the same order of magnitude (10-3

); therefore,

they all represent a comparable fraction of the statistical annual U.S. emissions. Note that the

normalized impacts for ODP are so small they can’t be seen on this graph (they are in the range

of 10-8

). Therefore, the ODP impacts are marginal when considered in the context of the total

U.S. emissions profile.

1200473.000 - 8193 30

4.2 Detailed Impact Assessment Results

The impact assessment results are calculated using characterization factors published by EPA’s

Tool for the Reduction and Assessment of Chemical and Other Environmental Impacts

(TRACI), version 2.1 (Bare 2011; EPA 2012).

Abbreviations for the impacts are described in

1200473.000 - 8193 31

Table 2-3 above, and are reproduced here for reference.

Environmental impact categories:

Acidification potential (AP) [H+ moles eq];

Eutrophication potential (EP) [kg N eq];

Global warming potential (GWP) [kg CO2 eq];

Ozone depletion potential (ODP) [kg CFC 11 eq];

Smog creation potential (Smog) [kg O3 eq];

Environmental indicators:

Primary energy demand (PED) [MJ lower heating value]

In the following graphs, the ranges of possible values for each scenario are represented by

floating bars. Because higher environmental burden is associated with the “worst case, the

worst-case scenario is represented by the upper limit of the stacked bar, and the best-case

scenario is represented by the lower limit. Any intermediate scenarios are then represented by

the borderline between different bar segments. An example results graph is shown in Figure 4-2.

1200473.000 - 8193 32

Figure 4-2. Example results graph

4.2.1 Isolation Gown

Results are shown in Figure 4-3 for the isolation gown scenarios. The functional unit for

comparison is 100 use cases.

1200473.000 - 8193 33

Figure 4-3. Isolation gown LCA results per 100 use cases

Reusables appear to have a lower environmental impact than disposables in every impact

considered, with the sole exception of ozone depletion, where the best-case disposable scenario

falls between mid-high and mid-low reusables. The reusable ozone depletion comes mainly

from upstream energy use in textile manufacturing.

Global warming impacts are shown in Figure 4-4, with burdens split across the different life

cycle stages. Breakdowns for additional impact categories are presented in the Annex.

1200473.000 - 8193 34

Figure 4-4. Isolation gown GWP breakdown

The disposables’ impacts are dominated by the raw materials (polypropylene) and

manufacturing of single-use gowns. The reusable products’ main impacts are use-phase washing

and manufacturing.

For disposables, the key difference between best- and worst-case global warming is the

manufacturing. For reusables, use-phase variation outweighs all other life-cycle phase

differences.

4.2.2 Wiper

Results are shown in Figure 4-5 for the wiper scenarios. The functional unit for comparison is

100 use cases.

1200473.000 - 8193 35

Figure 4-5. Wiper LCA results for 100 use cases

Reusables appear to have a lower environmental impact than disposables in every impact

considered, with the sole exception of eutrophication. The reusables eutrophication impacts

come from the assumption that washing towels releases 750 mg/L of biological oxygen demand

(BOD) to fresh water. This is a single data point provided by a TRSA member company and

may not be representative of many other laundry facilities.

Global warming impacts are shown in Figure 4-6, with burdens split across the different life-

cycle stages. Breakdowns for additional impact categories are available on request.

1200473.000 - 8193 36

Figure 4-6. Wiper GWP breakdown

The disposables’ impacts are dominated by the raw materials (polyester) and manufacturing of

single-use wipers. The reusable products’ main impacts come from use-phase washing.

For disposables, the key difference between best- and worst-case scenarios lies in the raw

materials. For reusables, differences across the scenarios are driven by use-phase energy

variability.

4.2.3 Napkin

Results are shown in Figure 4-7 for the napkin scenarios. The functional unit for comparison is

100 napkin uses, as opposed to meals. While multiple disposable napkins are sometimes used

during a meal, when a single cloth napkin would have otherwise sufficed, no quantitative data

regarding the prevalence of this behavior could be located, so we did not evaluate impacts based

on 100 meals (which could require more than 100 disposable napkins). Lacking these data, we

have evaluated the two products for 100 uses, ignoring any possible behavior that would

otherwise affect the outcome.

1200473.000 - 8193 37

Figure 4-7. Napkin LCA results for 100 use cases

For napkins, the best- and worst-case scenarios overlap each other based on the different

assumptions about pulp-making, weight and recycled content, and use-phase washing.

Considering the worst-case scenarios, disposables appear to have considerably higher impacts

than all reusable impacts. However, for those impacts, best-case and mid-low disposables have

an impact comparable to or lower than best-case and mid-low reusables. With no further

indication of the probabilities of the displayed scenarios, the conclusion has to be that each

product has the potential to render significantly higher burden than the other.

As described in Section 3.4.2, we chose to evaluate disposable napkins with the baseline pulp-

making process from the Environ report. Although additional scenarios could have been created

to widen the range of possible pulp-making impacts, we varied the paper-making impacts only

between high-impact and low-impact paper-making. Examining the life-cycle impacts in more

detail, we found that the pulp- and paper-making steps have a fairly similar share of the burden.

Table 4-1 shows the impacts of pulp- and paper-making for each of the disposable napkin

scenarios.

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Table 4-1. Impact of pulp and paper making in isolation

Disposable Process AP EP GWP ODP Smog

(H+ mol eq.)

(kg N eq.) (kg CO2 eq.) (kg R-11 eq.)

(kg O3 eq.)

Worst Case Paper making 3.246419 0.005825 5.519423 3.9E-09 0.66958

Pulp making 1.800657 0.007707 6.890515 8.57E-08 0.312114

Mid - High Paper making 1.401981 0.002515 2.383588 1.69E-09 0.289161

Pulp making 0.777622 0.003328 2.9757 3.7E-08 0.134788

Mid - Low Paper making 0.074116 0.000102 0.292971 1.39E-10 0.016631

Pulp making 0.318047 0.001326 1.184022 1.55E-08 0.057335

Best Case Paper making 0.078469 0.000108 0.310175 1.47E-10 0.017608

Pulp making 0.120259 0.000389 0.343596 7.16E-09 0.028633

Comparing the impacts of pulp and paper making for each impact category, the pulp- and paper-

making impacts are fairly close to each other (typically not more than double or smaller than

half of each other), with exceptions occurring for the mid-low disposable product. This product

is an exception, because it has 70% virgin pulp (fairly high impact) paired with low-impact

paper making, whereas the other scenarios have either 100% virgin pulp (high impact) paired

with high-impact paper making, or 100% recycled pulp (low impact) paired with low-impact

paper making.

If the impacts of pulp making were consistently higher than that of paper making, evaluating a

wider range of pulp data sets would improve the quality of the study. However, the impacts of

pulp and paper making were fairly close to each other, so the choice of using a single pulp data

set while varying paper making between high- and low-impact data sets is acceptable.

Global warming impacts are shown in Figure 4-8, with burdens split across the different life-

cycle stages. Breakdowns for additional impact categories are available on request.

1200473.000 - 8193 39

Figure 4-8. Napkin GWP breakdown

Disposables’ impacts are dominated by raw materials (paper), followed by paper manufacturing.

Reusables are dominated by use-phase washing.

For disposables, variation in raw materials burden is the key difference between the scenarios.

For reusables, variation in use-phase washing is the key difference between the scenarios.

1200473.000 - 8193 40

5 Interpretation

5.1 Identification of Relevant Findings

In summary, disposables’ impacts are driven by raw materials, followed by manufacturing

energy. Reusables’ impacts are dominated by use-phase washing and, to a limited extent, by raw

materials production.

Reusable isolation gowns appear to have a lower environmental impact than the disposable

products analyzed in every impact considered, with the sole exception of ODP. Reusable wipers

appear to have a lower environmental impact than the disposable products analyzed in every

impact considered, with the sole exception of EP. For napkins, the results are mixed - the best-

and worst-case scenarios overlap each other based on the different assumptions we make about

pulp-making, weight, recycled content, and use-phase washing.

5.2 Data Quality Assessment

Inventory data quality is judged by its precision (measured, calculated, or estimated),

completeness (e.g., unreported emissions), consistency (degree of uniformity of the method

applied on a study serving as a data source), and representativeness (geographic, temporal, and

technological).

To meet these requirements and ensure reliable results, first-hand industry data were used in

combination with literature and background LCA information from the GaBi 2012 database.

The LCI data sets from the GaBi 2012 database are widely distributed and used with the GaBi 6

Software. The data sets have been used in LCA models worldwide in industrial and scientific

applications, in both internal evaluations and many critically reviewed and published studies. In

the process of providing these data sets, they are cross-checked with other databases and values

from industry and science.

5.2.1 Precision and Completeness

Precision: Foreground data were based on primary data whenever possible.

Literature data were cross-checked against primary data or existing data from

confidential sources to ensure the highest precision available, because

primary data on manufacturing and product composition were often

unavailable. All background data were GaBi data with the documented

precision.

Completeness: Each unit process was checked for mass balance and

completeness of the emission inventory. No data were knowingly omitted. In

cases where primary data collectors could not provide inventory of similar

completeness, we used average or representative data from other providers to

supplement the gaps.

1200473.000 - 8193 41

5.2.2 Consistency and Reproducibility

Consistency: To ensure consistency, all primary data were collected with the

same level of detail, while all background data were sourced from the GaBi

databases. Allocation and other methodological choices were made

consistently throughout the model.

Reproducibility: Reproducibility is warranted as much as possible through

the disclosure of input-output data, data-set choices, and modeling

approaches in this report. Based on this information, any third party should

be able to approximate the results of this study using the same data and

modeling approaches.

5.2.3 Representativeness

Temporal: All primary data were collected for the year 2012. Some

literature data were considerably older, but cross-checks against confidential

data from other clients showed that the ranges published are still applicable.

All background data come from the GaBi 6 2012 databases and are

representative of the years 2006–2010.

Geographic: All primary and secondary data were collected specific to

North America when possible. The only notable exception is that kraft pulp

and papermaking inventory data were based on European best available

technology and then were modeled with North American LCIs. Geographic

representativeness is considered to be high.

Technological: All primary and secondary data were modeled to be specific

to the technologies or technology mixes under study. Where technology-

specific data were unavailable, proxy data were used (see Chapter 2.9).

Technological representativeness is considered to be good.

5.3 Completeness, Sensitivity, and Consistency

5.3.1 Completeness

All relevant process steps for each product system were considered and modeled to represent

each specific situation. The process chain is considered sufficiently complete with regard to the

goal and scope of this study.

5.3.2 Sensitivity Analysis on Single Parameters

The scenarios (worst, mid-high, mid-low, and best) are a combination of different parameter

values; therefore, the following sections show the effect on global warming of modifying each

1200473.000 - 8193 42

parameter in isolation. Each graph below shows GWP of the scenarios as bars on the primary y-

axis, and sensitivity factor as points on the secondary y-axis.

The sensitivity factor is calculated by dividing the percent change in GWP from the baseline by

percent change in the parameter being evaluated. In the isolation gown example, switching from

a 250-mile delivery distance to a 100-mile distance (a parameter change of –60%) yields a drop

in GWP from 162.87 to 158.51 (an impact change of –3%). The sensitivity factor is –3% / –60%

= 4%. In the case of parameters for which increasing value decreases impact (such as increasing

truck utilization or increasing number of lifetime uses), this inverse relationship is designated

with a negative sensitivity factor. The sensitivity factor for each scenario is shown as a dot on

the graph’s right-hand y-axis.

For scenarios where a combination of individual parameters are changed (i.e., worst vs. best

washing) or a binary parameter is changed (i.e., high-impact pulp vs. low-impact pulp), no

sensitivity calculation is possible.

5.3.2.1 Isolation Gown

The parameters evaluated for disposables include delivery distance, delivery utilization, product

weight, and manufacturing energy. The parameters evaluated for reusables include delivery

distance, delivery utilization, product weight, manufacturing energy, number of uses, and

washing scenario.

The effects of switching individual parameters are shown for disposables in Figure 5-1 and for

reusables in Figure 5-2. The worst-case gown scenarios are shown as the baselines, as defined in

Table 3-3. The other bars show the net GWP when changing a single parameter to its best-case

value while keeping all other parameters at their worst-case values.

1200473.000 - 8193 43

Figure 5-1. Disposable gown parameter sensitivity (GWP)

Figure 5-2. Reusable gown parameter sensitivity (GWP)

1200473.000 - 8193 44

Sensitivity analysis for disposables shows that reducing manufacturing energy from 5.16 to

1.31 MJ has the largest single effect on an absolute level, which is confirmed by its high

sensitivity factor. Improved washing has the largest effect for reusable wipers, followed by

reducing product weight from 12.8 to 10.8 oz and increasing the number of uses from 49 to 98.

For both disposables and reusables, changing the truck distance and utilization (amount of

laundry as a fraction of truck capacity) doesn’t affect the overall results in a meaningful way.

5.3.2.2 Wiper

The parameters evaluated for the disposables include delivery distance, delivery utilization, pulp

recycled content, and high- or low-impact pulp. The parameters evaluated for the reusables

include delivery distance, delivery utilization, product weight, and washing scenario.

The effects of switching individual parameters are shown for disposable scenarios in Figure 5-3,

and for reusables in Figure 5-4. Worst-case scenarios are shown as the baselines, as defined

above in Table 3-5. The other bars show the net GWP when changing a single parameter to its

best-case value while keeping all other parameters at their worst-case values.

1200473.000 - 8193 45

Figure 5-3. Disposable wiper parameter sensitivity (GWP)

Figure 5-4. Reusable wiper parameter sensitivity (GWP)

1200473.000 - 8193 46

Sensitivity analysis for disposables shows that switching from high-impact to low-impact paper

has the largest single effect on an absolute level, followed by increasing the recycled content of

the pulp. Other changes are minor. The largest reductions for reusables come from improved

washing. For both disposables and reusables, changing the truck distance and utilization

(amount of laundry as a fraction of truck capacity) doesn’t affect the overall results in a

meaningful way.

5.3.2.3 Napkin

The parameters evaluated for disposables include delivery distance, delivery utilization, product

weight, recycled content of the paper, and high- or low-impact paper making. The parameters

evaluated for reusables include delivery distance, delivery utilization, product weight, number

of uses, manufacturing energy, and washing scenario.

The effects of switching individual parameters are shown for disposable scenarios in Figure 5-5,

and for reusables in Figure 5-6. Worst-case napkins are shown as the baseline, as defined above

in Table 3-7. The other bars show the net GWP when changing a single parameter to its best-

case value while keeping all other parameters at their worst-case values.

Figure 5-5. Disposable napkin parameter sensitivity (GWP)

1200473.000 - 8193 47

Figure 5-6. Reusable napkin parameter sensitivity (GWP)

Sensitivity analysis for disposables shows that reducing product weight and switching from

high-impact to low-impact paper have the largest effects. Increasing recycled content shows a

considerable improvement as well. Improved washing has the largest effect for reusable napkins,

followed by reducing product weight from 50.8 grams to 32.1 grams. For both disposables and

reusables, changing the truck distance and utilization (amount of laundry as a fraction of truck

capacity) doesn’t affect the overall results in a meaningful way.

5.3.3 Consistency

All assumptions, methods, and data were found to be consistent with the study’s goal and scope.

Differences in background data quality were minimized by using LCI data from the GaBi 6

2012 databases. System boundaries, allocation rules, and impact assessment methods were

applied consistently throughout the study.

5.4 Conclusions, Limitations, and Recommendations

5.4.1 Conclusions

In summary, reusable isolation gowns appear to have clear environmental benefit compared to

the disposable products analyzed, except for ODP. The benefit comes from differences in raw-

material weight and manufacturing energy. For wipers, reusables appear to have a clear

environmental benefit compared to the disposable products analyzed, except for EP, which is

1200473.000 - 8193 48

linked to wastewater emissions during washing that may not be relevant to all facilities. For

napkins, reusables and disposables are similar if comparing best case products though

disposables have higher impact if comparing worst case products. Product weight has the

greatest influence on results, followed by the choice of high- or low-burden paper making,

recycled content, and use-phase washing variability.

5.4.2 Limitations and Assumptions

Only limited information on material manufacturing was taken from primary sources, so

literature and secondary data were cross-checked against confidential client manufacturing

details to validate the assumptions when possible. Reduced reliance on literature would have

increased the data quality, but was not possible within the scope, timeline, and budget.

We assume that a premium disposable napkin meets the same function as a reusable napkin,

though personal experience suggests that more than one disposable napkin may be used during a

meal, especially at the lighter end of the napkin spectrum. If additional disposable napkins were

used in a meal where only a single reusable were used, the disposable scenarios would all have

higher impact than the reusable scenarios.

5.4.3 Recommendations

In the cases of isolation gowns and wipers, reusables appear to provide a significant

environmental benefit compared to disposables. In the case of napkins, lighter weight disposable

products and reusables washed most efficiently exhibit the lowest per-wiping environmental

impacts. The importance of sourcing low-energy or recycled materials is especially pronounced

for products made from paper. Transportation is a small contributor, so only limited effort

should be spent on improving route efficiency or truck utilization.

1200473.000 - 8193 49

6 References

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Chemical and Other Environmental Impacts 2.0. Clean Technology

Environmental Policy. 2010

(Cotton, Inc., 2012) Cotton Inc. Life Cycle Assessment of Cotton Fiber and Fabric. 2012.

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about/LCI-LCA-Cotton-Fiber-Fabric/

(Earth First, 2013) Earth First Product Catalog.

http://www.earthfirstpaper.com/consumer.html . Last accessed in June 2014

(Environ, 2012) Environ International Corporation. Life Cycle Assessment of Deinked

and Virgin Pulp; Prepared for National Geographic. 2012

(EPA, 2012) Environmental Protection Agency (EPA). Tool for the Reduction and

Assessment of Chemical and other Environmental Impacts (TRACI)

version 2.1 User's Manual. 2012

(GP Essentials,

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(GP Preference,

2013)

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http://productcatalog.gp.com/Product.aspx?Pid=17016&Cat=6262&View=1 . Last accessed in June 2014

(Guinee, 2001) Guinée, J. B. (ed.). Handbook on life cycle assessment: Operational

guide to the ISO-standards. Centre for Milieukunde Leiden (CML).

2001.

(IVL, 2011) Swedish Environmental Research Institute (IVL). Life cycle assessment

of premium single-use and reusable napkins for restaurant dinners.

Prepared for Duni AB. 2011. Retrieved from

http://www.duni.com/Global/AboutUs/Environment/Documents/U3473_

Report_Duni-LCA-Critically-reviewed.pdf in June 2014

(ISO 14040, 2006) International Organization for Standardization. ISO 14040:2006.

Environmental Management – Life Cycle Assessment – Principles and

Framework.

(ISO 14044, 2006) International Organization for Standardization. ISO 14044:2006.

Environmental management -- Life cycle assessment -- Requirements

and guidelines.

(Joint Research

Centre, 2012)

Joint Research Centre. Best Available Techniques (BAT) Reference

Document for the Production of Pulp, Paper, and Board. Draft May 2012

http://www.earthfirstpaper.com/consumer.html

http://productcatalog.gp.com/Product.aspx?Pid=7752&Cat=6306&View=1



http://www.duni.com/Global/AboutUs/Environment/Documents/U3473_Report_Duni-LCA-Critically-reviewed.pdf

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(Meredith, 2011) Meredith, E. Black Ivory Napkin Test University of Kentucky Textile

Lab in 2011. (Malkan, 1994) Malkan, S. An Overview of Spunbonding and Meltblowing

Technologies. Paper presented at 1994 Nonwovens Conference. 1994

(McIlvane, 2009) McIlvaine Company. A White Paper on Performance, Cost Per Use, and

Environmental Impact of Single-Use and Reusable Surgical Gowns &

Drapes. 2009. Last retrieved from

http://mcilvainecompany.com/SURS/subscriber/Text/White%20Paper%208-17-09.pdf in June 2014

(PE

INTERNATIONAL

, 2011)

PE INTERNATIONAL. GaBi dataset documentation for the software-

system and databases, LBP, University of Stuttgart and PE

INTERNATIONAL GmbH, Leinfelden-Echterdingen. 2011

(http://documentation.gabi-software.com/)

(Pullman, 1997) Pullman, W et al. Environmental Assessment of Shop Towel Usage in

the Automotive and Printing Industries. (EPA). 1997

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http://mcilvainecompany.com/SURS/subscriber/Text/White%20Paper%208-17-09.pdf


Annex

Table 1. Isolation gown LCA results

Units Disposable

(Best) Disposable

(Worst) Reusable

(Best) Reusable (Mid–Low)

Reusable (Mid–High)

Reusable (Worst)

Acidification kg SO2 eq. 0.205 0.571 0.0521 0.0794 0.0974 0.133

Eutrophication kg Nitrogen eq. 0.12 0.191 0.0117 0.0181 0.0222 0.0327

Global Warming kg CO2 eq. 65.5 163 16.8 25.8 31.2 43.5

Ozone Depletion kg CFC-11 eq. 1.89E-08 5.55E-08 1.33E-08 2.03E-08 2.44E-08 3.24E-08

Primary Energy MJ 1680 3560 280 428 519 722

Smog Creation kg O3 eq. 2.66 6.28 0.68 1.04 1.26 1.75

Table 2. Wiper LCA results

Units Disposable

(Best) Disposable

(Worst) Reusable

(Best) Reusable (Mid–Low)


Reusable (Worst)

Acidification kg SO2 eq. 0.0108 0.0157 0.00409 0.00561 0.00572 0.00823

Eutrophication kg Nitrogen eq. 0.00146 0.00325 0.0517 0.106 0.113 2.22E-01

Global Warming kg CO2 eq. 6.01 8.89 1.49 2.21 2.29 3.57

Ozone Depletion kg CFC-11 eq. 1.14E-09 1.45E-09 3.66E-10 4.98E-10 5.04E-10 7.3E-10

Primary Energy MJ 87.1 118 21.6 33.4 34.5 55.1

Smog Creation kg O3 eq. 0.15 0.214 4.91E-02 0.071 0.0732 0.112

Table 3. Napkin LCA results

Units Disposable

(Best) Disposable (Mid–Low)

Disposable (Mid–High)

Disposable (Worst)

Reusable (Best)

Reusable (Mid–Low)


Reusable (Worst)

Acidification kg SO2 eq. 0.199672 0.393618 2.192283 5.097829 0.29866 0.375982 0.603508 0.750186

Eutrophication kg Nitrogen eq. 6.21E-04 6.21E-04 6.08E-03 1.41E-02 1.18E-03 1.58E-03 2.60E-03 3.39E-03

Global Warming kg CO2 eq. 1.30249 2.098093 6.685911 15.79989 1.793988 2.486705 3.980989 5.283447

Ozone Depletion kg CFC-11 eq. 7.30E-09 1.57E-08 3.87E-08 8.96E-08 1.34E-09 1.49E-09 2.38E-09 2.64E-09

Primary Energy MJ 10.03332 20.29294 122.9092 289.3114 30.34069 41.50548 66.30406 87.69368

Smog Creation kg O3 eq. 0.050612 0.07826 0.434996 1.013536 0.071859 0.093807 0.150755 0.192318

Normalization Factors

The table below shows normalization factors for the TRACI 2.1 method based on U.S.

emissions in 2008. These “equivalences” represent the annual per capita U.S. emissions profile.

The “factor” is the inverse of the equivalences. To calculate normalized results, the LCIA

results are multiplied by these factors (i.e., divided by per-capita U.S. emissions) for a

dimensionless normalized value.

Quantity Equivalences Unit Factor

TRACI 2.1, Acidification Air 90.8 kg SO2-Equiv. 0.011013

TRACI 2.1, Acidification Water 90.8 kg SO2-Equiv. 0.011013

TRACI 2.1, Ecotoxicity (recommended) 11100 CTUeco 9.01E-05

TRACI 2.1, Eutrophication Air 21.6 kg N-Equiv. 0.046296

TRACI 2.1, Eutrophication Water 21.6 kg N-Equiv. 0.046296

TRACI 2.1, Global Warming Air 24200 kg CO2-Equiv. 4.13E-05

TRACI 2.1, Human Health Particulate Air 24.2 kg PM2,5-Equiv. 0.041322

TRACI 2.1, Human toxicity, cancer (recommended) 5.07E-05 CTUh 19723.87

TRACI 2.1, Human toxicity, non-canc. (recommended) 0.00105 CTUh 952.381

TRACI 2.1, Ozone Depletion Air 0.161 kg CFC 11-Equiv. 6.21118

TRACI 2.1, Resources, Fossil fuels 17300 MJ surplus energy 5.78E-05

TRACI 2.1, Smog Air 1390 kg O3-Equiv. 0.000719

Review of the Report “Comparative Life Cycle Assessment of Reusable vs. Disposable Textiles” (Dated

June 17, 2014), Conducted for the Textile Rental Services Association of America by PE International

and Exponent

Review Statement Prepared by the Critical Review Panel:

Arpad Horvath (Chair), James Mellentine, Christopher M. Pastore

July 28, 2014

The review of this report has found that:

the approach used to carry out the LCA is consistent with the ISO 14040:2006 principles and

framework and the ISO 14044:2006 requirements and guidelines,

the methods used in the LCA appear to be scientifically and technically valid,

the interpretations of the results reflect the limitations identified in the goal of the study,

the report is transparent concerning the study steps and consistent for the purposes of the

stated goals of the study.

This review statement only applies to the report named in the title, available to the Critical Review

Panel on July 9, 2014, but not to any other document versions, derivative reports, excerpts, press

releases, and similar.

Arpad Horvath James Mellentine

Consultant, Berkeley, California Sustainable Solutions Corporation

Christopher M. Pastore

Philadelphia University